Learn more about FabCon and SQLCon 2026
The excitement surrounding this event reflects the same momentum we’re seeing across our data portfolio. Just two and a half years after Microsoft Fabric reached general availability, it’s already serving more than 31,000 customers and remains the fastest-growing data platform in Microsoft’s history. Fortune 500 companies like The Coca-Cola Company are already using Fabric at scale across their organizations.

Microsoft Fabric is helping us evolve our data foundation into a more unified, AI-ready platform. Combined with Power BI and capabilities like Fabric IQ, it enables the enterprise to turn data into intelligence and act on it faster.

Shekhar Gowda, Vice President of Global Marketing Technologies at The Coca-Cola Company
Our databases are accelerating just as quickly, with SQL Server 2025 growing more than twice as fast as the previous version.

Today, we’re thrilled to share how we are bringing the power of databases and Fabric together to form a truly converged data platform—one that unifies transactional, operational, and analytical data under a single, consistent architecture. I’ll also highlight how we’ve enhanced Fabric to help you transform data into the semantic knowledge AI needs to understand your business, powered by Fabric IQ and Power BI’s industry-leading semantic model technology.

Introducing the Database Hub in Microsoft Fabric
Databases sit at the heart of the enterprise data estate—a system of record powering applications, transactions, and mission‑critical insights. Yet as organizations scale across cloud, on‑premises, and edge environments, database estates have become increasingly fragmented and isolated. As AI places even greater demands on data estates, unifying databases under a single access point and control plane has become essential.

To address this challenge, Fabric is expanding its role as the central access point for enterprise data with the Database Hub in Fabric, now available in early access. Database Hub in Fabric provides a unified database management experience that brings together databases across edge, cloud, and Fabric into a single, coherent view. Teams now have one place to explore, observe, govern, and optimize their entire database estate—including Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server (enabled by Azure Arc), Azure Database for MySQL, and Fabric Databases—without changing how each service is deployed.

Built for scale, the Database Hub in Fabric introduces an agent‑assisted, human-in-the loop approach to database management. With built-in observability, delegated governance, and Microsoft Copilot-powered insights, teams can deploy intelligent agents to continuously reason over estate‑wide signals and surface what changed, explain why it matters, and guide teams toward what to do next. The result is a simpler, more confident way to manage databases at scale. Over time, this model enables database estates to become more proactive, resilient, and intelligent, laying the foundation for greater autonomy, while keeping humans firmly in control of goals, boundaries, and trust.

Learn more about Database Hub in Fabric and what’s new across Databases
Bringing databases together under a single management layer is a critical step as you prepare your estates for AI at scale. But it’s not the end of the journey. The challenge shifts from where data lives to how data is understood, connected, and activated across the enterprise.

Getting your data estate ready for AI with Fabric
As organizations move from traditional applications to AI‑powered, multi‑agent systems, the advantage is shifting away from the specific model you deploy. It now lies in the intelligence and context that allow agents to understand how your business is run, the state of your business, and your institutional knowledge to help take meaningful action.

This is the challenge Microsoft IQ is designed to address. Unlike point solutions on the market today, Microsoft IQ provides an intelligence layer that delivers shared, enterprise-grade business context to every agent. That context is built from three complementary sources: productivity signals from Work IQ, institutional knowledge from Foundry IQ, and live business data from Fabric IQ.

However, like the database layer, while the IQ context layer is a critical part of a successful, and healthy AI foundation, it is not the full story. Building a complete AI-ready data foundation requires investing in four core steps:

Unifying your data estate to eliminate silos and reduce architectural complexity.
Processing and harmonizing data so it becomes AI-ready, clean, connected, and structured for both operational and analytical use.
Curating semantic meaning to give agents contextual understanding, enabling them to interpret data the way your teams already do. This is where Microsoft IQ comes into play.
Empowering AI agents to act, applying that context to automate workflows, accelerate decisions, and transform operations end‑to‑end.
Unifying your data estate with Microsoft OneLake
Every AI initiative starts with the same fundamental challenge: understanding where your data lives and how to bring it together. Microsoft OneLake was built to solve that problem by unifying data across clouds, on-premises environments, and third-party platforms into a single logical data lake without unnecessary extracting, transforming, and loading (ETL), fragmentation, or duplicated copies.

Are my agents hunting for data?

Watch the podcast
Connecting to more sources than ever before
Today, we’re expanding Mirroring in Fabric to support even more systems our customers rely on. Mirroring for SharePoint lists and Dremio are now in preview with Azure Monitor coming soon, while mirroring for Oracle and SAP Datasphere are generally available—all of which are available as part of the core mirroring capabilities. We are also introducing extended capabilities in mirroring designed to help you operationalize mirrored sources at scale, including Change Data Feed (CDF) and the ability to create views on top of mirrored data, starting with Snowflake. Extended capabilities for mirroring will be offered as a paid option.

Shortcut transformations are also now generally available, allowing data to be shaped automatically as it connects to or moves within OneLake. You can convert formats such as Excel to Delta tables, now in preview, and apply AI-powered transformations.

Additionally, we are continuing to invest in open interoperability, ensuring OneLake works seamlessly with the platforms organizations already use. We are excited to announce the ability to natively read from OneLake through Azure Databricks Unity Catalog is now in public preview. We also recently announced the general availability of our interoperability with Snowflake.

I’m also excited to share that Auger, a rapidly growing supply chain platform designed to bring intelligence and automation to global operations, has built its platform on Fabric, with all data stored natively in OneLake. This architecture enables Auger customers to seamlessly access their operations data through OneLake shortcuts within their own Fabric environments and use the full power of the platform including Power BI, Fabric data agents, and more. Learn more in my blog, co-authored with Auger Chief Executive Officer Dave Clark.

Protect your data with OneLake security, now generally available
Security and governance remain foundational to OneLake. I’m thrilled to announce OneLake security will be generally available in the coming weeks, enabling data owners to define roles, enforce row- and column-level controls, and manage permissions through a single unified model that follows the data.

To learn more about these announcements, read the OneLake blog and the Fabric Data Factory blog.

Processing and harmonizing data with Fabric analytics
AI agents are only as reliable as the data you feed them. Before data can train or ground an agent, it must be integrated, cleaned, and structured, so the agent operates from consistent, trusted information. With industry-leading engines in Fabric like Spark, T-SQL, KQL, and Analysis Services, we can equip data teams to do exactly that.

Now, we are expanding these capabilities with the introduction of Runtime 2.0 in preview, purpose-built for large-scale data computation. It incorporates Apache Spark 4.x, Delta Lake 4.x, Scala 2.13, and Azure Linux Mariner 3.0 to power advanced enterprise workloads. Materialized lake views are also now generally available, simplifying medallion architecture implementation in Spark SQL and PySpark and enabling always up-to-date pipelines with no manual orchestration. In addition, a new agentic Copilot experience in notebooks delivers deeper context awareness, reasoning over your workspace, and generating code with greater speed and precision.

For real-time scenarios, we’re launching Microsoft Fabric Maps into general availability. Maps add geospatial context to your agents and operations by turning large volumes of location-based data into interactive, real-time visual insights.

For a comprehensive overview of these announcements and much more, read the Fabric Analytics announcement blog and the Fabric Real-Time Intelligence announcement blog.

Creating semantic meaning with Fabric IQ
Preparing raw data for AI is essential. The next step is transforming that data into meaningful, unified business context. That is where Fabric IQ comes in.

Fabric IQ unifies analytical data and operational data, including telemetry, time series, graph, and geospatial data, within a shared semantic framework of business entities, relationships, properties, rules, and actions. Instead of thinking in terms of tables and schemas, your teams and agents can operate on this framework, or ontology, aligned to how the business actually runs.

Fabric IQ ontologies will soon become accessible through an MCP server in preview, enabling agents to discover, understand, and act on this semantic layer. Ontologies can also serve as context sources for maps and soon in operations agents in Fabric, extending shared business context directly into operational decision-making and execution.

We are also excited to announce planning in Fabric IQ, a new enterprise planning capability that enables organizations to create plans, budgets, forecasts, and scenario models directly on top of Fabric’s semantic models. By complementing Fabric IQ’s ontologies with integrated planning, you get a complete, contextual view of your historical, real-time, and forward planning data. This allows users and agents to quickly answer what has happened, what is happening, and what should happen all from a single source. See this in action:

Finally, we recently announced a strategic partnership with NVIDIA to power the next generation of Physical AI by integrating Real-Time Intelligence and Fabric IQ with NVIDIA Omniverse libraries. The combined platform unifies real‑time operational data, business semantics, and physical simulation to enable organizations to optimize their physical operations in scenarios like intelligent digital twins, predictive maintenance, autonomous logistics, and energy optimization.

To learn more about all of our partner announcements, read the Fabric ISV announcement blog and the planning in Fabric IQ blog.

Enhancing the underlying Fabric IQ technology
Powering much of Fabric IQ’s rich experience is a combination of Power BI’s industry-leading, rich semantic model technology and graph in Fabric, our highly scalable graph database. Already delivering insights to more than 35 million active users, semantic models provide the ideal foundation for training agents through Fabric IQ. Now, with the general availability of Direct Lake on OneLake, your tables can be read directly from OneLake with native security enforcement, richer cross-item modeling, and import-class performance without data movement or refresh.

I’m also excited to share that graph in Fabric will be generally available in the coming weeks, enabling teams to visualize and query complex relationships across customers, partners, and supply chains.

To learn more, check out the Fabric IQ announcement blog and the Power BI announcement blog.

Empowering agents to act with Fabric data and operations agents
Frontier organizations are moving beyond general-purpose assistants and instead, adopting multi-agent systems composed of specialized agents. These agents are each grounded on specific data and reusable across different systems, allowing you to deliver more accurate, accelerated, and scalable outcomes.

To support your multi-agent systems, Fabric comes with built-in agent creation capabilities with Fabric data agents and operations agents. I’m excited to share that Fabric data agents are now generally available. Fabric data agents can be thought of as virtual analysts, aligned to specific domain data to support deeper analysis and deliver insights. Operations agents complement them by monitoring real-time data, detecting patterns, and taking proactive action.

Check out a quick demo of operations agents in Fabric:

These agents can be used across Fabric or as foundational knowledge sources in leading AI tools like Microsoft Foundry, Copilot Studio or even Microsoft 365 Copilot. To learn more about our AI announcements, check out the Fabric analytics blog covering data agents and the Fabric IQ blog covering operations agents.

Building mission-critical applications with developer experiences in Fabric
Developers building the next generation of AI applications need a comprehensive, cost-effective data platform that’s already integrated with your existing tools and workflows. Today, we are expanding Fabric’s developer tooling to meet that demand.

First, Fabric Model Context Protocol (MCP) is advancing with two major milestones. Fabric local MCP is now generally available, providing an open-source local server that connects AI coding assistants such as GitHub Copilot directly to Fabric. Alongside this, we’re introducing the public preview of Fabric remote MCP, a secure, cloud‑hosted execution engine that enables AI agents and automation tools to perform authenticated actions in Fabric.

We’re also enhancing our Git integration with selective branching, allowing developers to branch out for a specific feature and pull only the items they need. You also get improved change comparisons to more easily review recent updates, and new folder relationships which show how feature workspaces connect to source workspaces.

We’re also launching two open-source projects to help teams move faster with Fabric: Agent Skills for Fabric and Fabric Jumpstart. Agent Skills for Fabric is an open-source set of purpose-built plugins that let you use natural language in the GitHub Copilot terminal to harness the full power of Microsoft Fabric. Additionally, Fabric Jumpstart is designed to help you get off the ground with detailed guidance, reference architectures, and single‑click deployments for sample datasets, notebooks, pipelines, and reports.

Finally, we are announcing that the Fabric Extensibility Toolkit (FET), an evolution of the Workload Development Kit (WDK), is now generally available. Along with this release, we are enabling support for full CI/CD, variable library, and a new management experience in the Admin portal.

Read the Fabric Platform announcement blog
Migrating your existing Azure service to Fabric
As Fabric continues to grow in functionality, we are also simplifying the migration from other Azure services. In addition to our existing Synapse tooling, we are bringing new migration assistants for Azure Data Factory, Azure Synapse Analytics, and Azure SQL in public preview.

The new Fabric migration assistant for Azure Data Factory and Synapse Analytics helps move your existing pipelines and artifacts like Spark pools and notebooks into Fabric with minimal disruption. It’s designed to support incremental modernization, allowing teams to evaluate, convert, and optimize pipelines as they transition to Fabric. The migration assistant for SQL databases helps move SQL Server into Fabric by importing schemas through DACPACs, identifying and resolving compatibility issues with AI assistance, and guiding teams through assessment and data copy workflows for a smoother cutover.

See more Fabric innovation
Explore the AI shift with The Shift podcast
In addition to the announcements above, we are also rolling out a broad set of Fabric innovations across the platform. For a deeper look at the updates and what’s new this month, visit the Fabric March 2026 Feature summary blog, the Power BI March 2026 feature summary blog, and the latest posts on the Fabric Updates channel.

Explore additional resources for Microsoft Fabric
Sign up for the Fabric free trial. View the updated Fabric Roadmap. Try the Microsoft Fabric SKU Estimator.
Visit the Fabric website. Join the Fabric community. Read other in-depth, technical blogs on the Microsoft Fabric Updates Blog.
Read additional blogs by industry-leading partners
Sonata Software: Building an AI-ready data platform with data agents, ontology, and governance in Microsoft Fabric
Quadrant Technologies LLC: Real-Time Operational Intelligence in Microsoft Fabric: Deep Dive into RTI Capabilities, Anomaly Detection and Activator Alerting
Inspark: Why switch from Azure Synapse to Microsoft Fabric?
Esri: Unlock the power of location intelligence with ArcGIS for Microsoft Fabric
Dream IT Consulting Services: 8 Real-World Use Cases of Data Agents in Microsoft Fabric
UB Technology Innovations Inc.: From Data Platform to Decision Platform: How Microsoft Fabric and Copilot are Redefining Enterprise Analytics
Simpson Associates: Fabric Data Warehouse: Bringing Structure to Modern Data Strategies
Synapx Ltd.: Migrating Power BI to Microsoft Fabric Lakehouse with Medallion Architecture: A Strategic Imperative for Modern Construction Enterprises
Cloud Services: Real-Time Intelligence in Action: How Microsoft Fabric Helped Delfi Transform Its Newsroom
Cloud Services: Microsoft Fabric Data Agents: A New Reality
iLink Digital: Detect to Act in Seconds: How Real-Time Intelligence Is Rewriting the Rules of Emissions Management
Valorem Reply: How Nonprofits Are Rethinking Data with Microsoft Fabric

The post FabCon and SQLCon 2026: Unifying databases and Fabric on a single data platform appeared first on Microsoft SQL Server Blog.

This year is especially meaningful, as it marks the return of a Microsoft‑led SQL community event, while also showcasing how SQL continues to evolve as a critical part of Fabric. It is not just about new technology, but about reconnecting with each other and building the future of SQL together.

It’s inspiring to see the Microsoft SQL community continue to grow and engage, with user groups worldwide keeping conversations active across the SQL portfolio and a lot of customers using Microsoft SQL to innovate every day. With a comprehensive portfolio built on strategic common foundations and available across edge, PaaS, and SaaS, Microsoft databases form a unified platform for modern enterprise needs, whether you are migrating and modernizing, building cloud-native AI applications, or unifying your data.

Migrate and modernize with Azure SQL

Many of our customers are not modernizing in one big leap. You are evolving from SQL Server to hybrid and then to cloud services, and you want that journey to feel familiar, predictable, and low risk. That is exactly what Azure SQL is designed to deliver. Built on a consistent Microsoft SQL foundation from on premises to the cloud, Azure SQL brings AI capabilities directly into your database experience, along with enterprise‑grade security, high availability, and the flexibility to scale as your needs grow. Azure SQL is fully SQL compatible, delivers strong performance and low latency, and supports hybrid scenarios through Azure Arc.

AI agents are becoming an important accelerator for database migration and modernization at Microsoft, helping our customers reduce manual effort and move faster with more guided experiences across the journey. The general availability of GitHub Copilot in SSMS 22 is a great example of that investment in action: you can use the same GitHub Copilot experience you already use in Visual Studio and VS Code, now inside SQL Server Management Studio (SSMS), with chat and code assistance that helps you write, edit, and refactor T‑SQL more quickly and confidently. Whether you are a developer or database administrator (DBA), new to SQL or highly experienced, GitHub Copilot can support common workflows like improving queries and assisting with troubleshooting and administration tasks right where you work, and we are continuing to expand what it can do.

Today we are announcing savings plan for databases, a flexible, spend-based pricing option that helps you save up to 35%¹ vs. pay-as-you-go prices on a one-year commitment. Savings plan for databases is designed for modern, evolving database environments: Customers commit to a fixed hourly spend for one year and receive lower prices across eligible Azure database services. Savings are automatically applied to the highest-value usage each hour, helping reduce costs while supporting migration, modernization, and architectural change.

Build cloud-native AI apps at scale

Once you move to the cloud, the questions shift. How do you build faster, scale smarter, and unlock more value from your data without re‑architecting everything you have already built? That is where Azure SQL Database Hyperscale comes in.

With Azure SQL Database Hyperscale, customers gain better price-performance, elastic scale and resilience for any workload, without the cost or disruption of rewriting T‑SQL or reworking operational models. Its unique architecture, built on shared storage and multiple replicas, allows you to scale reads independently from writes. With built‑in HTAP isolation, applications can handle massive transactional and analytical workloads without complex redesign. New capabilities now in public preview extend that foundation even further, including the SQL MCP Server for securely connecting SQL data to AI agents and Copilots, as well as larger 160 and 192 vCore options for high‑throughput workloads.

We’re delivering faster, more capable vector indexes to power AI applications. Recent enhancements improve vector search performance and efficiency with no code changes required. With full insert, update, and delete support, vector indexes stay current in real time, enabling dynamic applications. Features like quantization, iterative filtering, and tighter query optimizer integration provide faster, more predictable results, helping teams build responsive AI experiences directly on their SQL data.

Temenos built its next‑generation banking platform, Temenos Core, on Azure using Azure SQL Database Hyperscale to achieve global scale, high availability, and resilient performance. The platform processes billions of transactions daily and more than 17,500 transactions per second at peak. By building on Hyperscale, Temenos reduced onboarding time, accelerated innovation, and shifted banks from worrying about downtime to competing on availability and digital innovation.

Unify your data estate with SQL database in Fabric

We continue to raise the bar on enterprise readiness for SQL database in Fabric by bringing enterprise-grade security and compliance capabilities directly into the platform. Today at SQLCon, we announced the general availability of features including SQL Auditing, Customer‑Managed Keys, and Dynamic Data Masking, and the preview of workspace‑level Private Link. We brought these enhancements to help customers meet strict governance and regulatory requirements without adding operational complexity. The result is confidence that your SQL workloads in Fabric are secure, compliant, and ready for production.

SQL database in Fabric is becoming even more powerful for AI‑driven applications. The same vector indexing enhancements available in Azure SQL Database Hyperscale are now built into SQL database in Fabric as well. Because both are powered by the same Microsoft SQL engine, customers benefit from consistent performance, capabilities, and innovation across the SQL portfolio—making it easier to build intelligent applications wherever their data lives.

Finally, moving to SQL database in Fabric is simpler than ever. The Migration Assistant now supports SQL database in Fabric as a target destination. It provides a Copilot-assisted experience that helps SQL developers assess readiness, migrate schema, identify compatibility issues, and copy data with less manual effort. By preserving familiar SQL skills and workflows, customers can modernize at their own pace while accelerating time to value on Fabric’s unified analytics and AI platform.

There is one more Fabric innovation that matters deeply for how we deliver Microsoft databases as a unified platform. As applications grow more sophisticated, most organizations now rely on a mix of SQL and NoSQL databases across cloud, on‑premises, and edge environments. Provisioning, monitoring, and maintaining health across a growing database fleet often requires multiple tools and portals, making it harder to see what’s happening and manage at scale.

To address this, we are introducing the Database Hub in Microsoft Fabric, now available in early access. The Database Hub provides a unified database management experience that brings together databases across edge, cloud, and Fabric into one coherent view. From a single place, database teams can explore, observe, govern, and optimize their entire estate, including Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server enabled by Azure Arc, and Azure Database for MySQL without changing how each service is deployed or operated.

Built for scale, the Database Hub introduces an agent-assisted, human-in-the-loop approach to database management. Intelligent agents continuously reason over estate-wide signals to surface what changed, explain why it matters, and guide teams toward what to do next, while built-in observability, delegated governance, and Copilot-powered insights help teams move from insight to action with greater confidence. With the Database Hub, teams spend less time navigating tools and more time enabling what comes next: unlocking deeper integration across applications, analytics, and AI from a single control plane for the Microsoft databases portfolio.

Database Hub is available today in early access. Sign up today and see how the Database Hub can bring clarity and control to your database estate.

Moving forward with the SQL community

SQLCon is about bringing the SQL community together. It is about rebuilding connections and shared learning. It also reflects our long-term commitment to SQL. With a comprehensive portfolio built on strategic common foundations and available across edge, PaaS, and SaaS, Microsoft databases provide a unified platform for modern enterprise needs, whether you are migrating and modernizing, building cloud-native AI applications, or unifying your data. We are investing in SQL for the future, alongside the community that continues to shape it.

Finally, SQLCon is coming to Europe! Join the global data and SQL community from 28 Sep – 01st October, 2026 in Barcelona, Spain for hands-on learning, expert insights, and real-world stories. Register to be a part of it. I can’t wait to see you there.

Additional SQL resources

• Microsoft Azure Summit: Migrate and Modernize with Agentic AI
• What is new about SQL database in Fabric
• Learn more about savings plan for databases

¹Customers may see savings estimated to be between 0% and 35%. The 35% savings estimate is based on one Azure SQL Database serverless running for 12 months at a pay-as-you-go rate vs. a reduced rate for a 1-year savings plan. Based on Azure pricing as of March 2026. Prices are subject to change. Actual savings may vary based on location, database service, and/or usage. 

The post Advancing agentic AI with Microsoft databases across a unified data estate appeared first on Microsoft SQL Server Blog.

Continue reading to learn about how three organizations—Thomson Reuters, Hexure, and CallRevu—each jumpstarted their transformation with migration of their on-premises workloads to Microsoft Azure. As a result, organizations were able to improve operational efficiency and accelerate AI-powered innovation. Their stories reveal how fully managed platform-as-a-service solutions like Microsoft Azure SQL Managed Instance helps organizations move from legacy constraints to a scalable and secure AI-ready foundation ready to power future possibilities.

Modernization at scale: Thomson Reuters  

For Thomson Reuters, one of the world’s most trusted providers of tax and accounting solutions, modernization was less of an option and more of a necessity. Supporting over 7,000 firms and 70,000 users during the peak of tax season required an infrastructure that was both robust and scalable. The company previously hosted more than 18,000 databases and over 500 terabytes of data on third-party servers, an approach that came with high costs, operational complexity, and challenges scaling to meet seasonal demand.  

By migrating this massive estate into Azure SQL Managed Instance from another cloud hosting environment, Thomson Reuters achieved modernization at scale. With programs like Microsoft Azure Migrate to support every step of the migration journey, and automation tools like PowerShell and Azure Resource Manager templates, they were able to streamline deployments and maintain performance while minimizing disruptions. Azure’s fully managed platform allowed Thomson Reuters to streamline database administration and automated key tasks like backups and updates. As a result, their teams could focus on delivering value to customers rather than managing infrastructure. Azure Virtual Desktop together with Windows 11 facilitated access to tax preparation applications, reducing complexity and costs.  

The benefits were immediate and significant. Thomson Reuters gained: 

• Consistent performance during seasonal peaks.
• Improved resiliency.
• Reduced support overhead.
• Optimized costs across licensing and infrastructure.  

Thomson Reuters now has a foundation for continued growth and the flexibility to scale its services as demand requires.

Operational efficiency and performance: Hexure  

While Thomson Reuters’ story highlights scale, Hexure’s migration shows the operational efficiency gains that come from moving to a fully managed platform with Azure SQL Managed Instance and Microsoft Azure App Service. Hexure provides digital solutions for insurance and financial services companies—managing sensitive customer information across many databases and applications.  

The company faced challenges with aging infrastructure that slowed down critical processes and demanded heavy manual intervention. Provisioning new customer instances, managing backups, and handling failovers was time-intensive. Processing delays made it harder to serve clients with the speed and reliability customers expect.  

Migrating to Azure SQL Managed Instance changed that equation. Hexure cut processing times by up to 97%, transforming overnight batch jobs into near-instant operations. Migration times were reduced by more than 80% thanks to built-in compatibility and automation. With Microsoft Azure Key Vault, Hexure could better manage cybersecurity and protection of their data. Features like point-in-time restore, automated backups, and geo-replication not only boosted resilience but also ensured compliance with industry regulations.  

Equally important, the move allowed Hexure to:  

• Onboard new customers in minutes versus hours.
• Deliver faster shipping cycles for features and platform improvements.
• Reduce management of infrastructure—including servers.

With migration, Hexure could now focus on innovation and customer service. For an industry where trust and responsiveness are critical, this operational leap forward directly translates into stronger client relationships.

Innovation with AI and insights: CallRevu  

CallRevu’s story illustrates the next frontier: innovation. CallRevu helps automotive dealerships improve lead conversion, follow-up, and customer experience by analyzing phone calls across more than 5,000 locations. Handling this volume of conversational data requires not only advanced analytics, but scalable platform. 

With a fully managed solution built on Azure SQL Managed Instance, Microsoft Azure Kubernetes Service together with Microsoft Azure AI services, CallRevu created a platform that goes beyond storing and managing data. It ensures reliable, scalable performance for call data and transcriptions, while services like Microsoft Azure OpenAI for real-time summaries and insights. This integration allows CallRevu to surface actionable insights in real time—helping dealerships connect marketing to results, improve agent performance, and ultimately drive more sales. 

The company also benefits from the operational simplicity that Azure SQL Managed Instance delivers. By migrating from their on-premises SQL Server environment, they were able to benefit from automated backups, scaling, and monitoring to reduce administrative overhead, while built-in security helps protect sensitive customer interactions. Data is mirrored in Microsoft Fabric allowing Power BI dashboards to generate real-time insights. With a strong and agile data foundation in place, CallRevu can focus on innovating faster—bringing AI-powered capabilities to an industry where customer engagement is a critical differentiator while also:  

• Increasing customer satisfaction by 10%.
• Saving USD500,000 annually in labor costs.
• Increasing lead conversion by 15%.

Take the next step in your transformation journey  

Modernization is not a one-time project—it’s a journey that is different for every organization. For some organizations, the first step is simply migrating off legacy servers. For others, it’s about rethinking how operations can run more efficiently. And for many, it’s about leveraging cloud and AI to create entirely new opportunities.  

The experiences of Thomson Reuters, Hexure, and CallRevu highlight how migration to a platform-as-a-service anchored on database solutions like Azure SQL Managed Instance supports every stage of that journey. By providing a managed, secure, and scalable cloud platform, backed by the tools and programs, organizations can migrate with confidence, operate more efficiently, and innovate faster.

Ready to get started? Here are some free tools you can start trying today: 

• Try Azure SQL Managed Instance free today. 
• Learn how Azure Migrate can help you get started.

Join Microsoft at PASS Data Community Summit 2025 to continue your learning journey and how Azure is making it easier than ever to start your transformation journey. Learn more on our sponsorship and presence.

The post Innovation spotlight: How 3 customers are driving change with migration to Azure SQL appeared first on Microsoft SQL Server Blog.

Adoption gains speed 

We’re seeing incredible momentum with SQL Server 2025 since its public preview debut at Microsoft Build. From lighting up community events like SQL Saturdays to being featured at SQLBits 2025 with CTP 2.1, the excitement is electric. SQL Server 2025 isn’t just keeping pace, it’s setting a new standard. Customers are adopting SQL Server 2025 twice as fast as SQL Server 2022 based on downloads of the public preview.

In the early adoption program, participants were asked to rank the SQL Server 2025 features they were most interested in testing. Built-in AI emerged as one of the top priorities, alongside performance and scalability enhancements. In addition, based on feedback from our preview customers, developer-friendly enhancements—especially the introduction of native JSON support—along with powerful T-SQL additions like regular expression support, have also been positively received—streamlining data processing and boosting developer efficiency. Enterprise customers like Entain, Mediterranean Shipping Company, Kramer & Crew, Schultz, and Bühler are already hands-on, exploring how SQL Server 2025 can power their next-gen applications. 

“As one of the largest SQL Server consulting firms in Brazil, we are excited about the AI features in SQL Server 2025, especially the potential for text processing that can benefit companies of all sizes. AI brings new ways to process and extract insights from data and with SQL Server being the core repository for many businesses, native AI features like embeddings, REST API support, and vector indexes are game changers. They eliminate the need for external vector databases, making AI integration more seamless and efficient.”

Rodrigo Ribeiro Gomes, Head of Innovation, Power Tuning

“SQL Server 2025 introduces seamless Azure and Arc integration and features, enhanced JSON and RegEx capabilities, and enhancements to database engine.”  

Shailesh Panday, Deputy Manager, IT, Buhler AG

Explore capabilities with new preview features

SQL Server 2025 introduces a new preview feature option, giving customers the flexibility to balance production stability with early access to innovation. When turned on, it unlocks access to upcoming features still in preview, enabling developers to test and evaluate new capabilities like vector indexing, improved text chunking, and change event streaming without impacting production workloads (a complete list of preview features is here).  

This opt-in model brings the agility of the cloud to on-premises SQL Server, empowering customers to innovate on their terms. Preview features are provided in alignment with Microsoft’s supportability guidelines. They are intended for evaluation and testing purposes only and are not recommended for use in production environments. The database itself in SQL Server 2025 remains as fully supported and is an essential component of the general availability release. Preview features are optional and designed to operate independently in preview mode. Enabling these features does not impact the stability or supportability of your database.  

SQL Server has traditionally used trace flags to enable or disable specific behaviors within the database engine. The new preview feature switch in SQL Server 2025 is fundamentally different from traditional trace flags. While trace flags are primarily used for debugging and diagnostics, often by DBAs or support engineers to control internal engine behavior, the preview feature switch is designed for developers to explore and test new, user-facing capabilities. Trace flags typically operate at the instance level, affecting the entire server, whereas the preview feature switch is a database-scoped configuration, offering more granular control and safer experimentation without impacting other workloads. Learn more about the preview features in the frequently asked questions.

New feature highlights

As SQL Server adoption on Linux continues to grow, we’re excited to introduce preview support for Ubuntu 24.04, one of the most widely used and trusted Linux distributions. This marks a significant step forward in our commitment to cross-platform flexibility and developer choice. By embracing the latest Ubuntu release, SQL Server 2025 ensures developers and IT teams can build and run modern, cloud-connected applications on a familiar and up-to-date Linux environment. 

PolyBase plays a critical role in enabling analytics scenarios by allowing SQL Server to query external data sources like Microsoft Azure Data Lake or Azure Blob Storage using familiar T-SQL. As many of SQL Server’s modern analytics capabilities are deeply integrated with Microsoft Azure services, secure and seamless access to cloud storage is essential. With preview support for Managed Identity authentication to Azure Storage, SQL Server 2025 takes a step forward in simplifying security and access management. This enhancement aligns with SQL Server’s decade-long track record as the most secure database and reinforces our commitment to enterprise-grade security. By eliminating the need for storing secrets or keys, Managed Identity makes it easier and safer for customers to build scalable, cloud-connected analytics solutions using PolyBase. 

Mirroring in Microsoft Fabric is a game-changing capability that unlocks seamless, near real-time analytics on operational data from SQL Server 2025. To help customers manage compute resources efficiently during the mirroring process, SQL Server now supports creating a dedicated Resource Governor (RG) pool. Each phase of mirroring—such as ingestion, transformation, and synchronization—can be assigned to a specific workload group, giving administrators fine-grained control over resource allocation. These workload groups can be placed in the same or different pools depending on capacity planning needs.  

Discover more 

SQL Server 2025

An AI-ready enterprise database with best-in-class security, performance, and availability.

Download RC0 today

• Download release candidate (RC0). 
• Learn more on Microsoft Learn.
• Discover what’s new in SQL Server 2025 in our latest Mechanics video.

The post Accelerating SQL Server 2025 momentum: Announcing the first release candidate appeared first on Microsoft SQL Server Blog.

SQL Server 2025

In November 2024, we announced the next major release of SQL Server: SQL Server 2025.

SQL Server 2025, now in private preview, includes capabilities to build AI applications including vector and AI model management, on-premises or in the cloud. We continue to invest in security, performance, and availability. Another exciting area of investment in SQL Server 2025 are developer features such as a JSON type, RegEx, Change Event Streaming, and REST API support. Sign-up to work with us for the next release. I look forward in 2025 as we ship a public preview and the general availability of this exciting major release.

Here are a few resources where you can learn more about SQL Server 2025:

• Announcing SQL Server 2025.
• SQL Server 2025: an enterprise AI-ready database platform.
• DBA Virtual User Group presentation on SQL Server 2025.

SQL Server enabled by Azure Arc

Azure Arc could be one of the most underused capabilities associated with SQL Server. The concept is amazingly simple. Instead of running SQL Server in Azure (that would be SQL Server in Azure Virtual Machine), you connect your existing SQL Server to Azure, whether it is running on-premises or another public cloud. Imagine using the Azure Portal to find out answers to questions like “What dbcompat levels are used across all my SQL Server instances?” Azure Arc has many other capabilities to help you manage your SQL Server instances, but a few I think you should look at are Microsoft Entra Authentication, Azure Migration, PAYG licensing, and ESU updates. Learn how to get started with Azure Arc.

Azure SQL

It is incredible to think that Azure SQL Database was launched almost 15 years ago as SQL Azure. Today Azure SQL is a brand that offers you the ability to run SQL Server in a Virtual Machine, a managed SQL instance, or a contained database. Each of these deployment options has continued innovations to accelerate development, deployment, and performance. SQL Server in Azure Virtual Machine continues to be a great option to lift and shift SQL Server, keep up to date with it here, but let’s look further at other Azure SQL options.

Azure SQL Managed Instance

The biggest new capability is Next-generation General Purpose service tier. This new deployment option offers a higher level of resources, better price/performance, more granular control of input/output (I/O) performance, and 500 databases per instance. I look forward in the future to seeing this become generally available. Keep up to date with all the latest announcements.

Azure SQL Database

We announced so many great new capabilities throughout 2024 including but not limited to:

• Hyperscale Serverless and Elastic Pools.
• Hyperscale performance and availability enhancements.
• New developer features like a JSON data type (which is also available in all flavors of SQL).

It might be time for you to rethink Hyperscale. With its new pricing model, Serverless and replica capabilities, this can be a great option to start a new database deployment and have it autoscale per your needs. And do not forget to try out Azure SQL Database for free (not a trial). Keep up to date with all the latest announcements.

SQL database in Fabric

Microsoft Fabric is a unified data platform. Up until now, most of the capabilities in Fabric were more centered around analytics. Now there is an operational database built within the Fabric, and it uses SQL Server!

SQL database in Fabric brings the power of Azure SQL Database deeply integrated into the Fabric ecosystem. Using the same database engine as SQL Server and Azure SQL, SQL database in Fabric is both familiar and innovative. Deploy a database in seconds, build a new AI application easily within the Fabric platform with CI/CD and GraphQL built-in. And all are integrated within the Fabric user experience and platform.

• Check out our Ignite presentation.
• Watch the Data Exposed series.
• We have excellent documentation to get you started. I especially like this SQL feature comparison and decision guides for SQL and Fabric data stores.
• Learn more in our Microsoft Mechanics video.

There is much more coming in this calendar year for SQL database in Fabric. Give it a spin today with a free Fabric trial capacity.

Tools and Copilots

We made big investments in 2024 in our tools and will continue to do more in this calendar year, but the most significant announcements were the revival of SQL Server Management Studio (SSMS) and new AI-assisted experiences.

SQL Server Management Studio

We accelerated the future investment of SSMS with enhancements to the latest release, SSMS 20. Proving that SSMS is back, we also announced a significant new preview release SSMS 21 which includes:

• A new shell based on the latest Visual Studio.
• New installer and update experience.
• Dark theme.
• 64bit support.
• Git support.

There is more to come in 2025 as we iterate on the current preview. Try out the new SSMS. In addition, we have a preview for a Copilot in SSMS.

AI-assistance in Azure SQL and SQL database in Fabric

We introduced an AI-assisted experience in the framework of Microsoft Copilot in Azure. Using your database context in the Azure Portal, you can type in prompts like, “my database is slow” and get fast and guided advice on performance troubleshooting scenarios. Try this out yourself. SQL Database in Fabric offers AI-assisted capabilities in the Query Editor and as a sidecar chat experience.

We believe AI-assisted capabilities can help both developers and administrators for SQL ground to cloud to fabric so we will continue to invest and innovate everywhere SQL exists in the future.

AI applications

The future of data-driven applications is to use AI. We believe the future is now, so we want to invest in capabilities inside the database engine to power your new AI applications, whether you are building retrieval-augmented generation (RAG) applications, chat-based applications, or AI agents. We also have a great solution outside of the SQL engine using Azure AI Search with SQL.

We believe SQL makes a compelling solution because you can build operational RAG applications using the security and scalability of the database engine using the familiarity of the T-SQL language. This includes access to AI models in Azure OpenAI, a new vector type, vector functions, and soon to be in the future vector search using vector indexes, built on the popular Microsoft vector indexing technology, DiskANN. SQL Server 2025 will include access to AI models on-premises or in the cloud. We also have solutions well integrated with frameworks like LangChain and Semantic Kernel.

Check out our demo at Microsoft Ignite to show AI applications for SQL everywhere they exist. Keep up with the latest for our AI application capabilities at intelligent applications, SQL AI samples, and this SQL AI workshop.

Fabric Mirroring

We have seen the rising popularity of Microsoft Fabric as a unified data platform. We want to be sure you can easily integrate your SQL data, wherever it exists, into Fabric. Therefore, we introduced the concept of Fabric Mirroring of Azure SQL Database. This provides a zero-ETL method to access your data separate from the operational database for near-real time analytics. This includes automatic changes fed into Fabric as you modify your source database and free Mirroring storage for replicas tiered to Fabric capacity. You can get started today for Azure SQL Database.

To ensure you can mirror any SQL database, we announced public preview for mirroring for Azure SQL Managed Instance and a private preview for SQL Server. You can also sign-up for the preview here.

Learn more at upcoming events

As you plan out the first few months of the year, consider these events where Microsoft and others from the community will teach you all of these new innovations.

VS Live Las Vegas 2025

This is one of the premier events focused on developers. Use the discount code WARD and register today.

Fabric Community Conference 2025

For the first time, the Microsoft Fabric Community Conference is putting SQL Server center stage. Join us at this incredible community event for a deep dive into SQL Databases in Fabric and get a preview of SQL Server 2025. The SQL Dream Team will be there. Shireesh Thota, Erin Stellato, Joe Sack, Muazma Zahid, Davide Mauri and I will be leading sessions. As well as SQL Community Legends – Denny Cherry, Grant Fritchey, Monica Rathbun, Anthony Nocentino, John Morehouse, Joey D’Antoni and more! Register with code MSCUST and get $150 off. Workshops sell out weeks in advance so save your spot now.

And we will be at more events in the upcoming calendar year. Here is to all our customers and community for a successful and momentous year in 2025 for SQL Server, from ground to cloud to fabric.

The post The year ahead for SQL Server: Ground to cloud to fabric appeared first on Microsoft SQL Server Blog.

By migrating their databases to Azure, customers like Ernst and Young are modernizing their data estate and leveraging cutting-edge cloud innovations. However, the migration process can be complex, whether moving within the same database management system (homogeneous) or between different systems (heterogeneous). Microsoft offers a suite of tools for migration to simplify the migration process. To further enhance the user experience, we are streamlining the Azure database migration tools ecosystem. This involves retiring certain overlapping tools to simplify finding the right tool and provide unified migration experiences across all phases of migration. As part of this effort, effective 12/15/2024 we are replacing some tools with unified experiences that offer capabilities across various migration stages in the drive to modernize their data estate and take advantage of innovation in the cloud.

Azure Database Migration Guides

Step-by-step guidance for modernizing your data assets

Learn more

With a refined set of tools, you can confidently plan, assess, and execute your database migration with minimal downtime, ensuring a smooth transition to Azure SQL. Post the 12/15/24, retirement date, Microsoft will stop supporting these tools for any issues that arise and will not issue any bug fixes or further updates. Here is the list of tools that are planned for retirement and Microsoft recommended replacement tools.

Microsoft recommended tools for migration to Azure SQL

With the retirement of Database Migration Assistant for Oracle (DMAO), Database Schema Conversion Toolkit (DSCT), Data Access Migration Toolkit (DAMT), Database Experimentation Assistant (DEA), the Azure database migration tooling ecosystem is greatly simplified. Here is Microsoft’s recommendation for database migration tools for customers moving to Azure SQL. 

Homogenous migrations (SQL Server to Azure SQL) 

If the SQL Server that will be migrated is already enabled by Azure Arc, you can use Arc capabilities to perform a migration assessment and get optimal Azure SQL Target recommendations. Additionally, SQL Server enabled by Azure Arc provides multiple Azure benefits to SQL Servers outside Azure like automated backups and patching, Microsoft Defender for SQL, inventory of instances and databases, and Entra ID support. By enabling these Arc features, you can leverage cloud automation and security for Azure SQL Server even before you migrate. 

If the SQL Server outside Azure is not inventoried yet, you can use Azure Migrate for discovery, assessment and business case to know the right Azure SQL targets for your on-premises SQL Workloads and to get the projected cost savings of migrating to Azure SQL.

To migrate SQL Server into an Azure Virtual Machine with the same configuration as the source, users can use Azure Migrate to perform lift and shift migrations. SQL Server on Azure Virtual Machines allows you to easily migrate your SQL Server workloads to the cloud, offering SQL Server’s performance and security along with Azure’s flexibility and hybrid connectivity to address urgent business needs. Later you can evaluate one of the Azure SQL PaaS targets (Azure SQL Managed Instance, Azure SQL Database) and modernize to a PaaS service for better cost and workload performance optimizations. 

If you have completed an assessment and are ready to move to Azure SQL Managed Instance or Azure SQL Database, you can start your migration journey with Azure Migrate, you can use Azure Database Migration service or Azure SQL Migration extension for Azure Data Studio can be used. 

If the SQL Server estate is already inventoried, users can use Azure SQL Migration extension for Azure Data Studio to complete the entire migration journey i.e., perform assessment, get Azure SQL Target recommendations and perform migrations.

Heterogenous migrations (non-SQL Server databases to Azure SQL) 

With the availability of Target Assessment and SKU recommendation capabilities in SQL Server Migration Assistant (SSMA) along with existing code conversion and migration capabilities, SSMA becomes a single tool that you need to use to migrate from other source database platforms like Oracle, DB2, SAP ASE, MySQL, Access to Azure SQL or SQL Server. 

Learn more about modernizing your databases with Azure

• Get step-by-step guidance for modernizing your Oracle and SQL Server databases to Azure in the Azure Database Migration Guides.
• Read about the Azure Migrate Assessment for Azure SQL to get an overview of SQL Server assessment process using Azure Migrate.
• Know how to complete end to end SQL Server to Azure SQL migration journey with Azure SQL Migration extension for Azure Data Studio. 
• Find documentation for SQL Server Migration Assistant (SSMA), a tool for assessing and automating migration from Microsoft Access, DB2, MySQL, Oracle, and SAP ASE.

The post Modernize your database with the consolidation and retirement of Azure Database Migration tools appeared first on Microsoft SQL Server Blog.

“With our migration to PaaS, we got what we wanted: greater scalability, reliability, security, agility in managing our IT infrastructure—and greater peace of mind—all without the cost and hassle of doing this ourselves,” 

Daniel Engberg, Head of AI, Data, and Platforms at Scandinavian Airlines System  

Migrate to Microsoft Azure

Boost productivity and enable innovation.

Read more

This blog post will guide you through several best practices our customers employed when faced with the SQL Server end-of-support moment. Customers have three choices for handling their out-of-support SQL Server workloads: moving or updating to Azure, upgrading to SQL Server 2022, or getting Extended Security Updates (ESUs) for additional preparation time. 

Migrate and modernize to Azure, a smooth path, a more powerful destination 

Migrating to a cloud platform is an essential step on the journey to modernization, and there are many choices. What makes SQL Server and Microsoft Azure SQL unique is that it’s built on the same engine, no matter where you deploy, which means you can build on your existing SQL experience while gaining the layered security, intelligent threat detection, and data encryption that Azure provides. 

Modernizing to Microsoft Azure SQL Managed Instance offers cost savings, scalability, security, seamless migration, productivity, and always up-to-date features. Some of the recent product highlights include Azure SQL Managed Instance Next-gen General Purpose, now in public preview, which supports twice as many Azure VMs configurations, making migration and modernization faster and easier than ever before for a larger number of customer scenarios. Customers can experience the full capabilities of managed SQL Server in the cloud at no cost for the initial 12 months with access to a General Purpose instance capable of accommodating up to 100 databases, along with 720 vCore hours of compute per month (non-accumulative) and 64 GB of storage through Azure SQL Managed Instance Free Tier, now in public preview. 

Modernizing your SQL Server workloads to Azure also presents a chance to utilize cutting-edge innovation like Microsoft Copilot. Microsoft Copilot in Azure has extended its capabilities to Microsoft Azure SQL Database with new skills designed to enhance the management and operation of SQL-based applications.  

Extending end-of-support time

If you are ready to move to the cloud but feel challenged to upgrade or modernize before the end of the support timeline, Extended Security Updates are available for free in Azure for SQL Server 2014 and 2012 and Windows Server 2012. Secure your workloads for up to three more years after the end of the support deadline by migrating applications and SQL Server databases to Microsoft Azure Virtual Machines. Free Extended Security Updates are available for Azure Virtual Machines including Microsoft Azure Dedicated Host, Microsoft Azure VMWare Solution, Nutanix Cloud Clusters on Azure, and Microsoft Azure Stack (Microsoft Azure Stack Hub, Microsoft Azure Stack Edge, and Microsoft Azure Stack HCI). Combining Extended Security Updates in Azure with Azure Hybrid Benefit further reduces your costs. With these pricing advantages, AWS is up to five times more expensive than Azure for SQL Server and Windows Server end-of-support workloads. 

In-place upgrade to SQL Server 2022 

Another way to stay protected is to upgrade your SQL Server to SQL Server 2022, the most Azure-enabled release yet. Get more out of your data with enhanced security, industry-leading performance and availability, and business continuity through Azure. 

SQL Server 2022 is the most Azure-enabled release of SQL Server, with continued innovation across performance, security, and availability. Gain deeper insights, predictions, and governance from your data at scale. Take advantage of enhanced performance and scalability with built-in query intelligence. 

Stay protected on-premises or in multi-cloud environments with Azure Arc 

Just as with SQL Server 2012, Extended Security Updates for SQL Server 2014 offers an enhanced cloud experience through Microsoft Azure Arc. First year coverage from Extended Security Updates started on July 10, 2024. With this more customer-centric approach, security updates will be natively available in the Microsoft Azure portal through Azure Arc. This also provides Azure benefits and flexible subscription billing for SQL Server 2014 workloads on-premises or in multi-cloud environments. 

We’re continuing to enhance the capabilities Azure Arc offers to Extended Security Updates. Just recently, physical-core licensing with unlimited virtualization was released for SQL Server 2012 and 2014 ESUs. For customers who need to maximize database performance or require security isolation and better resource management, physical core licensing provides a more cost-effective way to leverage Extended Security Updates via Azure Arc. 

Also, if you enabled ESU subscription in your production environment managed through Azure Arc, you can enable SQL Server ESU subscription in the non-production environment for free, through SQL Server Developer Edition or an Azure dev/test subscription. 

We encourage all our customers running SQL Server 2014, Windows Server 2012, and Windows Server 2012 R2 to start planning for the end of support. We have migration resources, best practices, and more, as well as a rich ecosystem of partners ready to help. To get started, please visit the following pages to learn more. 

Learn More 

• Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers 
• Get the full ROI and TCO reports from IDC: The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workload and The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads 
• Previous announcement on SQL Server 2014 End-of-Support moment: Protect SQL Server 2014 workloads with Azure flexibility – Microsoft SQL Server Blog

The post Modernize Microsoft SQL Server 2014 workloads with Azure appeared first on Microsoft SQL Server Blog.

During recent years, Azure has undergone significant evolution, marked by groundbreaking innovations like Microsoft Fabric and Azure Data Lake Storage. As we continue this journey, it remains imperative to keep evolving our approach on hybrid data storage, ensuring optimal empowerment for our SQL Server customers in leveraging the best from Azure.

Retirement of SQL Server Stretch Database 

On November 16, 2022, the SQL Server Stretch Database feature was deprecated from SQL Server 2022. For in-market versions of SQL Server 2019 and 2017, we had added an improvement that allowed the Stretch Database feature to stretch a table to an Azure SQL Database. Effective July 9, 2024, the supporting Azure service, known as SQL Server Stretch Database edition, is retired. Impacted versions of SQL Server include SQL Server 2022, 2019, 2017, and 2016.  

In July 2024, SQL Server Stretch Database will be discontinued for SQL Server 2022, 2019, 2017, and 2016. We understand that retiring an Azure service may impact your current workload and use of Stretch Database. Therefore, we kindly request that you either migrate to Azure or bring their data back from Azure to your on-premises version of SQL Server. Additionally, if you’re exploring alternatives for archiving data to cold and warm storage in the cloud, we’ve introduced significant new capabilities in SQL Server 2022, leveraging its data virtualization suite. 

The path forward 

SQL Server 2022 supports a concept named CREATE EXTERNAL TABLE AS SELECT (CETaS). It can help customers archive and store cold data to Azure Storage. The data will be stored in an open source file format named Parquet. It operates well with complex data in large volumes. With its performant data compression, it turns out to be one of the most cost-effective data storage solutions. Using OneLake shortcuts, customers then can leverage Microsoft Fabric to realize cloud-scale analytics on archived data.  

Our priority is to empower our SQL Server customers with the tools and services that leverage the latest and greatest from Azure. If you need assistance in exploring how Microsoft can best empower your hybrid data archiving needs, please contact us.

New solution FAQs

What’s CETaS? 

Creates an external table and then exports, in parallel, the results of a Transact-SQL SELECT statement. 

• Azure Synapse Analytics and Analytics Platform System support Hadoop or Azure Blob Storage.
• SQL Server 2022 (16.x) and later versions support CETaS to create an external table and then export, in parallel, the result of a Transact-SQL SELECT statement to Azure Data Lake Storage Gen2, Azure Storage Account v2, and S3-compatible object storage. 

What is Fabric? 

Fabric is an end-to-end analytics and data platform designed for enterprises that require a unified solution. It encompasses data movement, processing, ingestion, transformation, real-time event routing, and report building. Fabric offers a comprehensive suite of services including Data engineering, Data Factory, Data Science, Real-Time Analytics, Data Warehouse, and Databases. 

With Fabric, you don’t need to assemble different services from multiple vendors. Instead, it offers a seamlessly integrated, user-friendly platform that simplifies your analytics requirements. Operating on a software as a service (SaaS) model, Fabric brings simplicity and integration to your solutions. 

Fabric integrates separate components into a cohesive stack. Instead of relying on different databases or data warehouses, you can centralize data storage with Microsoft OneLake. AI capabilities are seamlessly embedded within Fabric, eliminating the need for manual integration. With Fabric, you can easily transition your raw data into actionable insights for business users. 

What is OneLake shortcuts?  

Shortcuts in OneLake allow you to unify your data across domains, clouds, and accounts by creating a single virtual data lake for your entire enterprise. All Fabric experiences and analytical engines can directly connect to your existing data sources such as Azure, Amazon Web Services (AWS), and OneLake through a unified namespace. OneLake manages all permissions and credentials, so you don’t need to separately configure each Fabric workload to connect to each data source. Additionally, you can use shortcuts to eliminate edge copies of data and reduce process latency associated with data copies and staging. 

Shortcuts are objects in OneLake that point to other storage locations. The location can be internal or external to OneLake. The location that a shortcut points to is known as the target path of the shortcut. The location where the shortcut appears is known as the shortcut path. Shortcuts appear as folders in OneLake and any workload or service that has access to OneLake can use them. Shortcuts behave like symbolic links. They’re an independent object from the target. If you delete a shortcut, the target remains unaffected. If you move, rename, or delete a target path, the shortcut can break. 

Learn more 

• Stretch Database
• Deprecated database engine features in SQL Server 2022
• Install an on-premises data gateway
• SQL Server in Microsoft Fabric? Use CETaS to move data!
• OneLake shortcuts
• CREATE EXTERNAL TABLE AS SELECT (CETaS)

Microsoft Fabric

Bring your data into the era of AI

Explore solutions

The post Announcing the retirement of SQL Server Stretch Database appeared first on Microsoft SQL Server Blog.

Azure SQL and SQL Server support building new generative AI experiences that become supercharged when combined with your data. In addition, SQL brings AI assistance to a new level with copilot experiences for both self-help and natural language to SQL capabilities.

In this blog post, I’ll share how you can get started with these new AI experiences—Azure SQL and SQL Server. First, check out our latest story on Microsoft Mechanics:

Responsible AI

Many conversations about AI starts with a statement on responsible AI. Microsoft has established a set of policies, research, engineering efforts, and principles to ensure AI technologies are adopted, implemented, and used in a responsible manner.

These principles include fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. Your data is your data. One promise for Microsoft is that private data of any user, including prompts and responses, are never used to fine tune a model that Microsoft hosts or implements.

Generative AI applications with your data

One of the motivations for generative AI applications is to become more productive, creative, and efficient through the generation of content in all forms: text, audio, and video. Many of today’s examples for generative AI applications involve the user of a natural language prompt and the interaction with a language model. Many of you have probably at some point used an application like ChatGPT or Microsoft Copilot which are great examples of generative AI applications.

Get smarter with your data

While these are great applications, they don’t know about your data. The combination of a generative AI application with your data, for example, stored in a database, can be quite powerful. Generative AI provides methods for smarter searching on your data. A common application pattern is to use language models with a prompt application to “chat with your data.” Using the concept of vector embeddings, language models allow you to get more precision on questions about your data. In addition, responses to questions are more tailored to your users and searches can often be faster because language models allow you to use the power of natural language. Generative AI applications with your data provide unique intelligence in an interactive manner, including conversations. Language models are trained to provide more context on your search, often giving you more (hence generated) content than you might normally get using common searching techniques within a database engine with a language like SQL.

Prompt engineering, Retrieval Augmented Generation fundamentals, and hybrid search

As you investigate how you can take advantage of generative AI with language models, there are two important concepts to understand:

Prompt engineering is the discipline of using high quality and descriptive prompts when interacting with a language model. The concept is simple. The better the prompt, the likelihood of a better response from the model. For example, let’s say you use Microsoft Copilot and type in a prompt like “What are the best steak restaurants in Fort Worth, Texas?” You will get a good list of steak houses in Fort Worth, Texas based on a search by Copilot of rankings across a broad set of searches. But what if you are on a bit of a tight budget? Instead of looking at the results from the prompt and trying to figure out what prices you can afford you could instead ask “I’m on a tight budget but want to eat at a good steakhouse in Fort Worth, Texas.” Now your results are more tailored for what you really want. And since you are interacting with a language model, it understands the phrase “tight budget” means you need choices that are good but affordable.

While this technique can be great if you are interacting with a model that is trained to help you search the internet, what about your own data? One prompt engineering technique to get smarter with your data is called Retrieval Augmented Generation (RAG). The concept of RAG is to search for information from a source of data and use those results to augment the prompt to the model. For Azure SQL and SQL Server, this could mean using standard SQL techniques to search for data using Transact-SQL (T-SQL), taking these results, and sending them along with the original prompt to the language model. This technique is simple and can be an effective way to get smarter with your data, and this can work with almost any type of data you search, not just SQL databases.

For Azure SQL and SQL Server, a more sophisticated technique is called hybrid search. With hybrid search, you can use the power of vector search combined with the query capabilities of your SQL data. Vector embeddings are numerical representations of data that capture semantic meaning and similarities. The key to embeddings with language models is that the model can generate embeddings based on data like text. This means you can take text data inside your SQL database and use a model to generate embeddings and then store these embeddings in your database. Now anytime you want to search for data inside the database, you can send a prompt to a language model which will generate embeddings for the prompt. And then you can use vector search techniques to compare the embeddings from the prompt with the embeddings stored in your database. You can then combine the vector search with other techniques you would normally use in T-SQL to find data in your database: a hybrid search.

There are methods today to use hybrid search completely inside the engine using T-SQL and outside the engine using Microsoft Azure AI Services or frameworks like LangChain or Semantic Kernel.

Get started quickly with Azure AI Services

One approach to get started quickly with no code required is to index your SQL database using Azure AI Search and then use Azure OpenAI Service to build a simple prompt app and “chat with your data” using a hybrid search technique.

You can use Azure AI Search to build an index based on a table in your SQL Server or Azure SQL database. When you build the index, you can apply a skillset to generate embeddings based on your data and store the result in the index. Now you can use Azure OpenAI with a prompt application to perform hybrid searches on your data. One example prompt application to perform simple testing is to use Azure AI Studio. In addition, as you change your SQL data, the index is automatically updated including the embeddings. The figure below shows the basic flow:

You can see this in action from the latest Microsoft Mechanics video or download a deck with demo recordings. One of the interesting aspects of this example is the method of changing the system message to direct the language model to respond in a unique way using the same data. This is also a great example of prompt engineering.

Learn more about Azure SQL in Azure AI Search.

Use hybrid search inside the engine with T-SQL

Let’s say instead of using a separate index, you would like to build generative AI capabilities for your application all inside the engine using T-SQL. You can do this in a very powerful way for Azure SQL Database today using a combination of vector embeddings, vector search, and other T-SQL search methods. This is a true hybrid search because you are using all the power of the SQL query processor together with a vector search. An example my colleague Davide Mauri has developed uses these techniques to help him find the best restaurant for one of this favorite Italian foods, focaccia bread.

Davide built an application that stores reviews from restaurants in the form of vector embeddings using Azure OpenAI Service with Azure SQL Database Representational State Transfer (REST) API inside the engine. With this in place, he can take any prompt to search for the best focaccia bread and use the same technique to generate embeddings for the prompt. Then, he can use a new T-SQL vector_distance function to perform a similarity search. The true power of SQL is possible because Davide built queries to combine this vector search with other criteria from spatial types, the new JSON data type, and the new Regular Expression (RegEx) T-SQL capabilities.

You can see a diagram of how these techniques are combined together below:

You can see this demo in action in our Microsoft Mechanics video or download a deck with demo recordings. You can learn more about the new JSON data type (preview). You can also sign-up to preview the new vector search capabilities and RegEx in Azure SQL Database.

Building generative AI applications using frameworks

There are other methods to build generative AI applications with Azure SQL and SQL Server using frameworks such as:

• LangChain:
  LangChain is an open-source framework to orchestrate AI applications with language models. You can use programming languages such as Python and JavaScript to build your own generative AI application. LangChain supports the SQL Agent Toolkit which allows you to interact with a SQL database using natural language prompts. The toolkit integrates the connection to your database with a language model to generate SQL queries based on natural language prompts. You can see an example of this in the blog post “Building your own DB Copilot for Azure SQL with Azure OpenAI GPT-4.”
• Semantic Kernel:
  Semantic Kernel is an open-source SDK to allow you to build AI applications in C#, Python, and Java, interfacing with many common models in the industry such as OpenAI, Azure OpenAI, and Hugging Face. A library has been built to allow a Semantic Kernel application to interact with Azure SQL Database (and use the new vector search capability) called the SQL Connector.

See a full range of SQL and generative AI examples.

The age of copilots

Microsoft has transformed the industry and how we work and live with a new set of AI assisted experiences called Microsoft Copilot. Copilots are AI companions that work everywhere you do and intelligently adapt to your needs.

Use Copilots where you live

I realize there seem to be copilots everywhere. It is hard to keep track. Microsoft is investing in Copilot experiences in almost every product or service. Use the product or service you normally do and see what Copilot can offer. For example, if you have Microsoft 365, use Copilot for Microsoft 365 naturally within Microsoft Teams or any Office product or service. I personally use Microsoft Copilot in my Edge browser or on the app on my phone for any search experience I need today—web or work related.

Microsoft Copilot in Azure

The primary resource to manage and explore Microsoft Azure is the Azure portal. You can now use Microsoft Copilot in Azure within the Azure portal to manage, deploy, and troubleshoot Azure resources. Azure SQL Database is one of the most popular Azure resources in the world, so we have built two distinct experiences within the Copilot in Azure framework using natural language for self-guided assistance and T-SQL query authoring:

Microsoft Copilot in Azure integration

One of the strengths of SQL Server is the deep built-in telemetry within the engine all accessible through T-SQL. This includes Dynamic Management Views (DMV) and Query Store. These rich, traditional capabilities shine through now in Copilot. For example, you can prompt with Copilot a general statement like “My database is slow” and Copilot, based on your permissions, will access real-time diagnostic data, in the context of your database, to help you quickly navigate difficult, and often vague, performance problems. Here is an example:

You can then continue a conversation with Copilot to tune the query causing the problem. There are many different skills that Copilot can help you all in the context of your database. Learn about all the possibilities of Copilot skills in Azure SQL Database (preview).

Natural language to SQL

The T-SQL query language has so many great capabilities and possibilities. But the open nature of T-SQL also leads to difficulties in crafting queries to meet the need of your application. Along comes a copilot experience to allow you to “chat” with your database using natural language in the context of your database and schema: table, columns, and key relationships. A simple example is being able use a natural language statement to generate a query that typically requires several joins over multiple tables like the following:

Learn more how to use natural language to SQL.

You can see both experiences in action in our Microsoft Mechanics video or download a deck with demo recordings.

Innovations moving forward

We are just beginning with SQL and AI. We have innovations for the future planned for enhancements with AI services, enhancements for deep integration for vector search, and enhanced Copilot experiences for SQL Server. Stay tuned for future blog posts showing all of these innovations.

Learn more today

Here are more resources for you to learn more about SQL and AI:

• Explore the capabilities of Azure SQL Database.
• Keep track of SQL and AI at our one-stop documentation hub.
• Keep track of all of our SQL and AI examples.
• Showcase your own demos using our decks with demo recordings built-in.
• Read our team’s blog on developer experiences for SQL including the latest AI examples at Azure SQL Devs’ Corner.
• To see all this in action, check out our new Microsoft Mechanics video.
• Learn the essentials to building a SQL generative AI application.
• Check out the comprehensive blog post from Sanjay Mishra to explore the power of generative AI applications with Azure SQL Database.
• Learn more about Copilot in Azure SQL Database experiences from Joe Sack’s Data Exposed episode.
• Check out our Microsoft Build 2024 sessions:
  • Power AI apps and develop rich experiences with Azure SQL Database
  • The power of AI and Copilot for Azure Databases

Azure SQL

Migrate, modernize, and innovate with the modern SQL family of cloud database services

Start your journey

The post Getting started with delivering generative AI capabilities in SQL Server and Azure SQL appeared first on Microsoft SQL Server Blog.

We’ve been on the road the last couple of weeks at MVP Summit, SQLBits and Fabric Con, connecting with customers talking about the value of migration and modernization. We want to dig into specifically, how Azure can deliver real business value through cost optimization and streamlined productivity for their Windows Server and SQL Server deployments when they migrate to Azure. 

We’ve helped countless organizations migrate their SQL Server and Windows workloads to Azure a critical 1^st step in any transformation initiative. The move can help improve cybersecurity posture and business continuity, boost productivity, and lay the foundation for AI and other highly scalable data innovations, while automating updates, backups, and other time-consuming IT tasks. 

Modernize and lower total cost of ownership (TCO) 

Migration is a business strategy that pays off. In The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workload,¹ organizations that migrated to Azure SQL Managed Instance and Microsoft Azure SQL Database can get up to 406 percent return on investment over 3 years and can expect a 30-percent reduction in TCO over 5 years, protecting an additional $6.85 million in annual revenue.

A separate study found that customers that migrated both Windows Server and SQL Server workloads to Azure generated more value. According to The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads,² by optimizing costs, operations, and business opportunities, companies gained $15.85 million in total annual benefits while also increasing IT security efficiency by 43 percent with cloud tools and automation.

Azure SQL

Migrate, modernize, and innovate with the modern SQL family of cloud database services.

Start today

A smooth path to migration, a more powerful destination

Migrating to a cloud platform is an essential step on the journey to modernization, and there are many choices. 

What makes SQL unique is that it’s built on the same engine, no matter where you deploy, which means you can build on your existing SQL experience while gaining the layered security, intelligent threat detection, and data encryption that Azure provides. And as we shared with customers at SQLBits, there’s now an even more powerful option available for customers looking to leverage the full PaaS experience. Azure SQL Managed Instance Next-gen GP  brings significantly improved performance and scalability to power up your existing Azure SQL Managed Instance fleet, and help bring more mission-critical SQL workloads to Azure. With close to 100 percent feature compatibility with SQL Server, Azure SQL Managed Instance is the recommended choice to migrate and modernize SQL apps at scale and at your own pace.

Another option many of our customers start with is by running their Windows Server workloads on Azure Virtual Machines, benefiting from a simplified, managed experience and cloud-native support for SQL Server, .NET apps, and Remote Desktop Services. Or you can modernize your entire Windows Server estate, choosing from more than 200 Azure services and capabilities, including support for hybrid environments. 

Take the first step or the next: You have choices

When it comes to migration, Azure meets you where you are with options for moving on-premises workloads and for developing new cloud solutions. For example, many organizations start by moving Windows Server workloads to Azure Virtual Machines, enabling them to easily scale to support new developments and more efficiently manage peak loads. Hokkoku Bank took this step, migrating its Windows Server–based estate to Azure as part of a cloud-first initiative. Azure supports the bank’s modernization plans and helps provide a disaster recovery solution in an earthquake-prone region.  

Correios de Portugal, the country’s postal service, migrated its Windows Server workloads to Azure Virtual Machines backed by Azure SQL, which provides a smooth path to a cost-effective, highly scalable, fully managed PaaS database. It’s the best choice for modernizing your apps and getting the most out of your existing investments.

Many of our database customers move to SQL Server on Azure Virtual Machines for the cost benefits on top of the scalability and resilience of Azure. As an example, healthcare software manufacturer Allscripts migrated on-premises applications to Azure SQL Database Managed Instance when possible, but another 600 on-premises VMs needed a different migration approach. Allscripts moved them to SQL Server on Azure Virtual Machines, a quick, low-risk step for workloads it plans to optimize and modernize later. The lift-and-shift approach can be an easy first   step in your cloud journey.

Azure also offers hybrid solutions that bridge your on-premises and cloud resources. For example, you can move or extend on-premises VMware environments using Azure VMWare Solution. You can even use the free Windows Admin Center tool to manage across Windows Server environments—physical, virtual, on-premises, in Azure, or in a hosted environment—at no additional cost. To get started with a Windows Server migration, start discovering and assessing on-premises resources using the free Azure Migrate tool.

Watch the Migrate to Innovate digital event on demand and learn the business benefits of migrating to Azure.

Try it for free 

If you want to know how your workload will perform before migrating, try these Azure offers and get started building that proof-of-concept.  

• Try Azure SQL Managed Instance for free. For 12 months, you can get up to two instances per Azure subscription, 750 vCore hours of compute per month, and 32 GB data storage and 32 GB backup storage per month. 

• Try Azure SQL Database for free. Test and develop applications or run small production workloads for free. This offer provides the first 100,000 vCore seconds, 32 GB of data, and 32 GB of backup storage per month at no charge for the lifetime of your subscription. 

• Try Windows Server in the cloud with an Azure free account. Extend your existing Windows Server datacenter and try out popular services free for 12 months. 

Learn more about Azure SQL

Stay tuned for more migration announcements in the coming months. To get started now: 

• Get the full ROI and TCO reports from IDC: The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workload and The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads.

• Review the benefits of migration in Better on Azure: The benefits of using Azure for Windows Server and SQL Server workloads. 

• Discover why cloud economics make sense and get greater return on your investment. 

1. IDC report, The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workloads, IDC #US51073123, August 2023. 
2. The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads

The post Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers appeared first on Microsoft SQL Server Blog.